Smart space environments have become of interest in recent years, in particular in the context of pervasive computing, which has the objective of seamlessly embedding computing, or information processing, in everyday life. In particular in relation to the Internet of Things, a communication network, such as the internet, does not only link computers and terminals, but any kind of surrounding objects and their virtual representations, and implies various technologies such as wireless technologies, computer technologies, and electronic identification technologies. The linked objects may be identified by electronic labels, and connected to the internet via communication terminals, thus allowing for receiving, storing, processing, and transfer object-related data. Objects, interfaces, and computers or terminals linked within a smart space may be conceived to service specific user requirements. Smart spaces also feature communication means to connect the virtual representations of the objects within a system of interconnected smart spaces.
The objects may be located in physical or virtual spaces and are typically associated with services they provide. Examples for smart spaces and the contained objects include the following:                an office or a company department, comprising telephones, computers, printers, video projectors, etc.,        a hotel or a residence, including alarms, heaters, remote controls, televisions, labeled chairs, etc.,        an airport, a shopping centre, or another public building, including computers or servers, sensors, etc.        
In order to benefit from a service provided by an operated or otherwise used object, a service discovery request is launched in the smart space or in a plurality of interconnected smart spaces to discover services complying to the request, e.g. linked to the location of the object providing the service. Typically, the request and the provided services are described using semantic descriptions, e.g. relying on concepts from a number of ontologies.
A current centralized technique consists in regrouping all semantic service descriptions and processing the incoming service request, for example, by comparison of their concepts. However, this method is very cost intensive in terms of computational time and memory, and may suffer from a “performance bottleneck” due to its centralized nature.
Another, so-called peer-to-peer, approach can be employed where simple smart spaces (i.e., physical rooms including the objects) are considered. However, this solution requires supplementary intelligence to correctly address location-intensive requests (i.e., requests for several services being hosted in several different rooms).
According to the foregoing, there exists a need for improved service discovery in the context of interconnected smart spaces hosting a vast number of available objects and their associated services. An efficient and fast service discovery mechanism making economical use of computational and memory resources is highly desirable.